Triple
T31910544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Sultan Mahmud Shah IV |
E814669
|
entity |
| Predicate | hasPrimarySchoolOfLaw |
P17978
|
FINISHED |
| Object | Shafi‘i school |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Shafi‘i school | Statement: [House of Sultan Mahmud Shah IV, hasPrimarySchoolOfLaw, Shafi‘i school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySchoolOfLaw Context triple: [House of Sultan Mahmud Shah IV, hasPrimarySchoolOfLaw, Shafi‘i school]
-
A.
studiedLawIn
Indicates that a person received legal education or training at a particular institution or location.
-
B.
studiedLawBy
Indicates that one entity pursued or received legal education under the instruction, supervision, or at the institution represented by the other entity.
-
C.
hasLegalEducationInstitution
Indicates that an entity is associated with or linked to an institution that provides legal education.
-
D.
majorSchoolOfLaw
chosen
Indicates that a particular school of law is a primary or dominant legal tradition or framework associated with an entity.
-
E.
containsLawSchool
Indicates that one entity includes or encompasses a law school as part of its structure, contents, or composition.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f348f109d88190b5005372c53d2fcd |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a009273634c8190b5b9c87053b56760 |
completed | May 10, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_6a0092171230819096e4274dd97e0410 |
completed | May 10, 2026, 2:11 p.m. |
Created at: May 1, 2026, 12:01 a.m.